Papers with Code 아카이브

2D Semantic Segmentation

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하위 태스크

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평가표

11

보존된 평가 기록

42

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/samra-irshad/3d-boundary-constrained-networks

공식 코드

Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks

https://github.com/samsunglabs/swissdino

공식 코드

Swiss DINO: Efficient and Versatile Vision Framework for On-device Personal Object Search

https://github.com/samtzai/tecnalia_weee_hyperspectral_dataset

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Hyperspectral Dataset and Deep Learning methods for Waste from Electric and Electronic Equipment Identification (WEEE)

https://github.com/sangminwoo/Local-to-Global-Interaction-Networks-SGG

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Tackling the Challenges in Scene Graph Generation with Local-to-Global Interactions

https://github.com/sangminwoo/Temporal-Span-Proposal-Network-VidVRD

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What and When to Look?: Temporal Span Proposal Network for Video Relation Detection

https://github.com/saniaesk/skin-lesion-segmentation

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Skin Lesion Segmentation Improved by Transformer-based Networks with Inter-scale Dependency Modeling

https://github.com/santiago2205/lssqps

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Learning Semantic Segmentation with Query Points Supervision on Aerial Images

https://github.com/sarashoouri/efficientmtl

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Efficient Computation Sharing for Multi-Task Visual Scene Understanding

https://github.com/sarihust/sammed

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Leveraging SAM for Single-Source Domain Generalization in Medical Image Segmentation

https://github.com/sayaknag/unbiasedsgg

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Unbiased Scene Graph Generation in Videos

https://github.com/sbrunoberenguel/fredsnet

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FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions

https://github.com/scailab/paser

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Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation

https://github.com/scarecrow0/sgtr

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SGTR: End-to-end Scene Graph Generation with Transformer

https://github.com/scenediffuser/Scene-Diffuser

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Diffusion-based Generation, Optimization, and Planning in 3D Scenes

https://github.com/schmiddo/d2conv3d

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D^2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos

https://github.com/scott-yjyang/hcdg

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HCDG: A Hierarchical Consistency Framework for Domain Generalization on Medical Image Segmentation

https://github.com/scott-yjyang/vivim

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Vivim: a Video Vision Mamba for Medical Video Segmentation

https://github.com/scut-dlvclab/gpt-4v_ocr

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Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation

https://github.com/scut-ml-guo/mimo

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Evaluation of Multi-indicator And Multi-organ Medical Image Segmentation Models

https://github.com/seanzhuh/awesome-open-vocabulary-detection-and-segmentation

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A Survey on Open-Vocabulary Detection and Segmentation: Past, Present, and Future

https://github.com/seedatnabeel/Uncertainty-Decision-Support-Healthcare

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MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts

https://github.com/segmentationblwx/sssegmentation

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ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation

https://github.com/selgroup/sit-hss

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Hierarchical Superpixel Segmentation via Structural Information Theory

https://github.com/senyh/ucmt

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Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation

https://github.com/seonghoon-yu/pseudo-ris

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Pseudo-RIS: Distinctive Pseudo-supervision Generation for Referring Image Segmentation

https://github.com/seonghoon-yu/zero-shot-ris

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Zero-shot Referring Image Segmentation with Global-Local Context Features

https://github.com/sephirex-x/latentdriver

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Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous Driving

https://github.com/seq-to-mind/semi-style-transfer

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Learning from Bootstrapping and Stepwise Reinforcement Reward: A Semi-Supervised Framework for Text Style Transfer

https://github.com/serbanstan/mas3-continual

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Online Continual Domain Adaptation for Semantic Image Segmentation Using Internal Representations

https://github.com/serbanstan/uda-medical-image-segmentation-sfs

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Domain Adaptation for the Segmentation of Confidential Medical Images

https://github.com/sercant/mobile-segmentation

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An efficient solution for semantic segmentation: ShuffleNet V2 with atrous separable convolutions

https://github.com/serdarch/sernet-former

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SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks

https://github.com/serenos/di-v2x

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DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object Detection

https://github.com/serenos/lwsis

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LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving

https://github.com/seung-b/fl-psg

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Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation

https://github.com/seung-lab/abiss

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Large-scale image segmentation based on distributed clustering algorithms

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.